metadata
license: cc-by-nc-4.0
datasets:
- kyujinpy/KOR-gugugu-platypus-set
language:
- en
- ko
base_model:
- yanolja/KoSOLAR-10.7B-v0.2
pipeline_tag: text-generation
KoSOLAR-v0.2-gugutypus-10.7B

Model Details
Model Developers
- DongGeon Lee (oneonlee)
Model Architecture
- KoSOLAR-v0.2-gugutypus-10.7B is a instruction fine-tuned auto-regressive language model, based on the SOLAR transformer architecture.
Base Model
Training Dataset
Model comparisons
- Ko-LLM leaderboard (YYYY/MM/DD) [link]
Model | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
---|---|---|---|---|---|---|
KoSOLAR-gugutypus | NaN | NaN | NaN | NaN | NaN | NaN |
- AI-Harness evaluation [link]
Model | Copa | Copa | HellaSwag | HellaSwag | BoolQ | BoolQ | Sentineg | Sentineg |
---|---|---|---|---|---|---|---|---|
0-shot | 5-shot | 0-shot | 5-shot | 0-shot | 5-shot | 0-shot | 5-shot | |
KoSOLAR-gugutypus | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
Implementation Code
### KoSOLAR-gugutypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "oneonlee/KoSOLAR-v0.2-gugutypus-10.7B"
model = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
tokenizer = AutoTokenizer.from_pretrained(repo)